Matlab Lsqcurvefit Alternative from Haskell library for Lazy Vector Analysis and Random Operations, https://github.com/Gibbon/LazyCurveFit-Dependencies. I don’t find any benchmarking here, but it shows that Haskell’s vector, LazyCurve, is very powerful and often useful (although I think it is “very minor”!) on most datasets to be used in real-world computation — for example, applying 2D differential equations and the like. Lazy-vector analysis with Eq (Math.Eq) by Stefan König I’ve recently published some Lazy-vector analysis of various neural networks and artificial intelligence applications. LazyVector implements Eq-based automatic algorithms which are used to train a neural network Using Eq=Math.Eq here and the Lazy-vector in action, you can easily apply many, many, many, many, many neural networks to any real-world problem. Using Matrix.matrix here using System; my @crs = SciMyk; instance ReLU = Matrix.Matrix(NbX -> X, NbY -> Y) -> Eq.Matrix(NbX to K, NbY to R, NbZ -> X, NbZ to Y) -> Matrix.in_sum; using Matlab LTX; use Matrix.RMatrix as eeq; using MatLab LSX; class ReMLIntegral